Last week’s Strata + Hadoop World conference in San Jose, Calif., ended on a perfect note! Over the years the event has evolved from merely discussing the power of Big Data analytics to actually implementing emerging technologies to discover relationships within that data.

After gathering my notes from the conversations that I had with the attendees who visited our booth, I can sum up my Strata experience with these two takeaways:

Graph databases are the key to extracting more value from Big Data

A lack of scalability is the primary limitation of other graph technologies

It’s no surprise that more enterprises are facing technical challenges when it comes to discovering patterns and connections within their large datasets—a challenge that graph databases were designed to solve. According to Forrester Research, “Graph databases will be the fastest-growing area in database management systems, with more than 25% of enterprises using graph by 2017.” In the last several years, I have noticed that the companies are transitioning out of the awareness stage into the evaluation stage of determining which graph platform is best suited for their business needs.

However, during this evaluation, it is clear that increased graph technology adoption requires massive scalability. Organizations with petabytes of data are dealing with graphs of up to trillions of nodes and edges, and Objectivity’s ThingSpan is purpose-built for that extreme level of scale. As a highly distributed graph analytics platform natively integrated with Hadoop and Spark, ThingSpan can solve some of the most demanding and complex Big Data challenges in the enterprise today.

We’ll be discussing some of these challenges, specifically in regards to the financial services industry, in our upcoming webinar, “Scaling High Finance Graphs with Spark,” on Tuesday, April 19, at 10:00am PT. You can register for the webinar by clicking here.

In this webinar, Leon Guzenda, Chief Technical Marketing Officer at Objectivity, and guest Mike Gualtieri, Principal Analyst at Forrester Research, will explain the technical challenges involved when supporting massive volumes of data in a mixed workload environment, and how to leverage open technologies, such as Spark, HDFS, and GraphX, to enable real-time graph analytics and relationship discovery for financial uses cases, such as smart trading, regulation and compliance, and cybercrime prevention.

You can learn more about all of our upcoming events here, and if you’re interested in tackling Big Data with graph technology, contact us for a demonstration of our platform ThingSpan. We look forward to hearing from you!